title: Prediction and imitation in speech.
abstract: It has been suggested that intra- and inter-speaker variability in speech are correlated. Interlocutors have been shown to converge on various phonetic dimensions. In addition, speakers imitate the phonetic properties of voices they are exposed to in shadowing, repetition, and even passive listening tasks. We review three theoretical accounts of speech imitation and convergence phenomena: (i) the Episodic Theory (ET) of speech perception and production (Goldinger, 1998); (ii) the Motor Theory (MT) of speech perception (Liberman and Whalen, 2000; Galantucci et al., 2006); (iii) Communication Accommodation Theory (CAT; Giles and Coupland, 1991; Giles et al., 1991). We argue that no account is able to explain all the available evidence. In particular, there is a need to integrate low-level, mechanistic accounts (like ET and MT), and higher-level accounts (like CAT). We propose that this is possible within the framework of an integrated theory of production and comprehension (Pickering and Garrod, 2013). Similarly to both ET and MT, this theory assumes parity between production and perception. Uniquely, however, it posits that listeners simulate speakers' utterances by computing forward-model predictions at many different levels, which are then compared to the incoming phonetic input. In our account phonetic imitation can be achieved via the same mechanism that is responsible for sensorimotor adaptation; i.e., the correction of prediction errors. In addition, the model assumes that the degree to which sensory prediction errors lead to motor adjustments is context-dependent. The notion of context subsumes both the preceding linguistic input and non-linguistic attributes of the situation (e.g., the speaker's and listener's social identities, their conversational roles, the listener's intention to imitate).
authors.affiliation: Department of Psychology, University of Edinburgh Edinburgh, UK.
authors.forename: Chiara
authors.initials: C
authors.lastname: Gambi
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Pickering
keywords: convergence; forward models; imitation; prediction error; simulation